config.py

# Configuration for the Gradio User Study App

# --- File and Folder Names ---
DATA_FOLDER = "data"  # Main folder containing domain subfolders
BACKGROUND_IMAGE_NAME = "input_bg_bb.png"  # Standard name for background input
FOREGROUND_IMAGE_NAME = "input_fg.jpg"  # Standard name for foreground input
PROMPT_FILE_NAME = "prompt.txt"  # Standard name for the prompt file
# Names for the output images from different models.
# These should be actual filenames present in each sample's folder.
MODEL_OUTPUT_IMAGE_NAMES = {
    "baseline": "cp_bg_fg.jpg",
    "kv-edit": "kvedit.jpg",
    "tf-icon": "tf-icon.png",
    "dit-editor": "alphanoise0.05_timesteps50_QTrue_KTrue_VFalse_taua0.4_taub0.8_guidance3.0_all-layers.png",
}
# Names to display for each model in the UI (can be different from filenames)
MODEL_DISPLAY_NAMES = {
    "baseline": "Model A",
    "kv-edit": "Model B",
    "tf-icon": "Model C",
    "dit-editor": "Model D",
}

# --- Data Collection ---
RESULTS_CSV_FILE = "user_preferences.csv"
CSV_HEADERS = [
    "session_id",
    "timestamp",
    "domain",
    "sample_id",
    "prompt",
    "input_background",
    "input_foreground",
    "displayed_order_model_1", # To store which model was shown in 1st position
    "displayed_order_model_2", # To store which model was shown in 2nd position
    "displayed_order_model_3", # To store which model was shown in 3rd position
    "displayed_order_model_4", # To store which model was shown in 4th position
    "preferred_model_key",     # The key of the preferred model (e.g., "model_a")
    "preferred_model_filename" # The filename of the preferred image
]
SAMPLES_PER_DOMAIN = 3 # Number of samples to show from each domain per user session

# --- Hugging Face Hub ---
HF_DATASET_REPO_ID = "matsant01/dit-editor-collected-preferences"  # Replace with your actual repo ID
HF_TOKEN = None  # Set this if your dataset is private, or use HF_HUB_TOKEN env var
PUSH_INTERVAL_HOURS = 0.25 # Interval in hours to push results to the Hub

# --- UI Configuration ---
IMAGE_DISPLAY_SIZE = (300, 300) # (width, height) for displaying images
APP_TITLE = "Image Composition User Study"
APP_DESCRIPTION = """
Please look at the input foreground and background images, and the text prompt used for generation, then choose the composed image that you prefer the most.
You consider:
* 📸 **subject consistency**: does the subject resemble the one in the foreground image? Or is it just a similar object/animal?
* 🖼️ **background preservation**: is the background image correctly preserved?
* 🎨 **style blending**: is the subject style correctly adapted to the one of the background?
"""
FOOTER_MESSAGE = "Thank you for participating!"

# --- Other ---
SESSION_ID_LENGTH = 16 # Length of the randomly generated session ID

# --- Paths ---
BACKUP_FOLDER = "backup"